1. Field
This disclosure generally relates to the field of audio delivery. More particularly, the disclosure relates to a receptacle that receives a computing device with an audio delivery component.
2. General Background
With the increasing use of computing devices, various outlets (e.g., stores, shopping centers, conference centers, etc.) provide users with the ability to perform tasks at physical locations through such devices. For instance, kiosks physically situated in stores allow users to purchase items, view account information, provide payment, etc.
Yet, such kiosks are typically limited in the amount of data that can be provided to users in auditory form for a variety of reasons. Firstly, kiosks are typically located in busy areas that are prone to significant amounts of noise; such an environment is not conducive to effectively providing a user with data. To counteract such effects, users may have to have information repeated or may even discontinue use of the kiosk. Secondly, the audio emanating from kiosks is typically so widespread that other users can easily hear data only intended for the user at a kiosk—a significant privacy concern.
As a result, audio delivery components situated at conventional kiosks are ineffective for providing quality audio to users. Therefore, current audio hardware components do not filter noise adequately for an optimal user experience.
In the mobile context, mobile computing devices (e.g., smartphones, tablet devices, smartwatches, etc.) are being increasingly used to provide communication between users over various communication modalities (e.g., voice over IP (“VOIP”), video, etc.). For instance, a software application (local, cloud-based, etc.) used by such mobile computing devices may communicate with systems (e.g., desktops, servers, etc.) or other mobile computing devices.
The software application may be used for chat, social networking, language interpretation, and/or telemedicine. As the users of the software application in such contexts are often situated in environments with significant background noise (e.g., a hospital), the quality of the audio being delivered to, and emanating from, the mobile computing device is often diminished. The recipient of the audio received by a microphone of the mobile computing device often receives an audio signal having the intended audio intermixed with noise, and the recipient of the audio emanating from the speakers of the mobile computing device often cannot hear the audio signal well given the background noise. For example, medical professionals performing telemedicine in a hospital environment often communicate with mobile computing devices mounted on stands that may not be at closes distances to the medical professionals; thereby, allowing for the potential of background noise being intermixed with the intended audio content.
Various software-based solutions have been implemented in current configurations to filter out such intermixed noise. Yet, such software-based solutions are often computationally intensive; as a result, computational resources are expended on software-based filtering processes, which may result in delayed audio provided to the users of such configurations. Further, such software-based solutions often output less than optimal audio quality. For example, parts of a conversation between two users may be inadvertently labeled by software-based solutions as part of the background noise; thereby, being removed from the audio content.
Therefore, software-based solutions may lead to audio delivery delays resulting from slower processing times, diminished audio quality resulting from audio content being deleted, etc. In an environment where communication time and accuracy is paramount (e.g., telemedicine), software-based solutions are often ineffective where significant background noise is possible. Therefore, current audio filtering software configurations do not optimally deliver audio to a user in such contexts.